Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: Hispanic 
Marital status: Single 
Religion: Nothing 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Go to gigs;Exercise;Use social media;Go to museums and galleries;Do arts and crafts;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;GitHub Copilot;Google Gemini 
LLM use cases: Translation;Paraphrasing or finding synonyms;Generic chatbot conversation;Analyze data;Play games 
Contexts of LLM use: Work;School/University;Personal;Entertainment 
Prompt 1: Create flashcards based on the following information
Prompt 2: List the steps of the scientific method, and add a couple paragraphs expanding on each
Prompt 3: Extract every verb from the following text:
Prompt 4: What types of cinematic shots are there?
Prompt 5: Generate ideas for a D&D fantasy setting
Prompt 6: Be my DM for a roleplaying game. Here's some basic details about the world, fill out details based on these guidelines:
Prompt 7: What is Maslow's hierarchy of needs? Is it still used today?
Prompt 8: Generate 10 different fantasy names for an Orc character
Prompt 9: Generate town names for D&D , similar but not identical to forgotten realms names
Prompt 10: What are the layers of the atmosphere and what makes each one distinct from those immediately above and below it?